A wireless communication device in a communication system communicates directly (e.g., point to point) or indirectly with other wireless communication devices. For direct/point-to-point communications, the participating wireless communication devices tune their receivers and transmitters to the same channel(s) and communicate over those channels. For indirect wireless communications, each wireless communication device communicates directly with an associated base station and/or access point via an assigned channel.
Each wireless communication device participating in wireless communications includes a built-in radio transceiver (i.e., transmitter and receiver) or is coupled to an associated radio transceiver. Typically, the transmitter includes one antenna for transmitting radiofrequency (RF) signals, which are received by one or more antennas of the receiver. When the receiver includes two or more antennas, the receiver selects one of antennas to receive the incoming RF signals. This type of wireless communication between a transmitter with one antenna and receiver with one antenna is known as a single-output-single-input (SISO) communication.
Well known communications systems provide a range extension on a SISO system by reducing the data rate and, as a result, increase the symbol duration and/or increasing transmit power. However, increasing transmit power can lead to increase interference to other users sharing the network. The preferred method for improved range reception does not lead to decreased network capacity. For popular multicarrier systems, such as SISO WLANs, range improvement is achieved by taking an 802.11a/802.11g signal and cutting the symbol rate. Specifically, the 802.11ah is the range extension an amendment of the IEEE 802.11-2007 wireless networking standard. The goal of the amendment is to optimize the rate vs. range performance of the specific channelization. One proposed method to achieve range extension is by down sampling the 802.11a/802.11g physical layer into 26 channels. When the symbol clock is divided by 26, each symbol duration becomes 104 μsec and the corresponding rate for each subcarrier becomes 12 kbps. Keeping the other system parameters, the same, (e.g. number of data carriers, cyclic prefix percentage, etc.), the bandwidth for a signal is reduced as well the integrated thermal noise power at the receiver. Therefore, for the same transmit power as 802.11a/802.11g, the thermal noise floor is decreased by 10*log 10 (26). This results in a 14 dB “gain” in the sensitivity of the receiver which is equivalent to at least 5 times improvement in the range of an over existing WLAN. What is needed is a communication device, system and method that increases the transmission range of existing WLAN for specific applications without impacting the data rate and adds flexibility to address new markets for high connectivity environments. A suitable invention would improve transmission characteristics of targeted devices without an increase in interference of other nearby the wireless systems and devices. Therefore, what is needed is a method for improved range reception that does not lead to decreased network capacity or increased susceptibility to interference of the wireless device.
Generally speaking, transmission systems compliant with the IEEE 802.11a and 802.11g or “802.11a/g” as well as the 802.11n standards achieve their high data transmission rates using Orthogonal Frequency Division Modulation (OFDM) encoded symbols mapped up to a 64 quadrature amplitude modulation (QAM) multi-carrier constellation. In a general sense, the use of OFDM divides the overall system bandwidth into a number of frequency sub-bands or channels, with each frequency sub-band being associated with a respective sub-carrier upon which data may be modulated. Thus, each frequency sub-band of the OFDM system may be viewed as an independent transmission channel within which to send data, thereby increasing the overall throughput or transmission rate of the communication system. Similarly, multi-code spread spectrum system comprised of perfectly orthogonal high-speed chaos spreading codes transporting independent modulated data can be used to increase its overall throughput or transmission rate of the SISO system. The high-speed “spreading signals” belong to the class of signals referred to as Pseudo Noise (PN) or pseudo-random signal. This class of signals possesses good autocorrelation and cross-correlation properties such that different PN sequences are nearly orthogonal to one other. The autocorrelation and cross-correlation properties of these PN sequences allow the original information bearing signal to be spread at the transmitter.
Transmitters used in the wireless communication systems that are compliant with the aforementioned 802.11a/802.11g/802.11n standards as well as other standards such as the 802.16a IEEE Standard, typically perform multi-carrier OFDM symbol encoding (which may include error correction encoding and interleaving), convert the encoded symbols into the time domain using Inverse Fast Fourier Transform (IFFT) techniques, and perform digital to analog conversion and conventional radio frequency (RF) upconversion on the signals. These transmitters then transmit the modulated and upconverted signals after appropriate power amplification to one or more receivers, resulting in a relatively high-speed time domain signal with a high peak-to-average ratio (PAPR).
Transmitters used in direct sequence spread spectrum (DSSS) wireless communication systems such as those compliant with commercial telecommunication standards WCDMA and CDMA 2000 perform high-speed spreading of data bits after error correction, interleaving and prior to symbol mapping. Thereafter, the digital signal is converted to analog form and frequency translated using conventional RF upconversion methods. The combined signals for all DSSS signals are appropriately power amplified and transmitted to one or more receivers.
Likewise, the receivers used in the wireless communication systems that are compliant with the aforementioned 802.11a/802.11g/802.11n and 802.16a IEEE standards typically include an RF receiving unit that performs RF downconversion and filtering of the received signals (which may be performed in one or more stages), and a baseband processor unit that processes the OFDM encoded symbols bearing the data of interest. The digital form of each OFDM symbol presented in the frequency domain is recovered after baseband downconverting, conventional analog to digital conversion and Fast Fourier Transformation of the received time domain signal. Whereas receivers used for reception for DSSS must de-spread the high signal after baseband downconverting to restore the original information signal band but yields a processing gain equal to the ratio the high speed signal to information bearing signal. Thereafter, the baseband processor performs demodulation and frequency domain equalization (FEQ) to recover the transmitted symbols, and these symbols are then processed with an appropriate FEC decoder, e.g. a Viterbi decoder, to estimate or determine the most likely identity of the transmitted symbol. The recovered and recognized stream of symbols is then decoded, which may include deinterleaving and error correction using any of a number of known error correction techniques, to produce a set of recovered signals corresponding to the original signals transmitted by the transmitter.
To further increase the number of signals which may be propagated in the communication system and/or to compensate for deleterious effects associated with the various propagation paths, and to thereby improve transmission performance, it is known to use multiple transmission and receive antennas within a wireless transmission system. Such a system is commonly referred to as a multiple-input, multiple-output (MIMO) wireless transmission system and is specifically provided for within the 802.11n IEEE Standard and 3GPP LTE Advanced standard. As is known, the use of MIMO technology produces significant increases in spectral efficiency, throughput and link reliability, and these benefits generally increase as the number of transmission and receive antennas within the MIMO system increases.
In particular, in addition to the frequency channels created when using OFDM, a MIMO channel formed by the various transmit and receive antennas between a particular transmitter and a particular receiver includes a number of independent spatial channels. As is known, a wireless MIMO communication system can provide improved performance (e.g., increased transmission capacity) by utilizing the additional dimensionalities created by these spatial channels for the transmission of additional data. Of course, the spatial channels of a wideband MIMO system may experience different channel conditions (e.g., different fading and multi-path effects) across the overall system bandwidth and may therefore achieve different signal-to-noise ratio (SNRs) at different frequencies (i.e., at the different OFDM frequency sub-bands) of the overall system bandwidth. Consequently, the number of information bits per modulation symbol (i.e., the data rate) that may be transmitted using the different frequency sub-bands of each spatial channel for a particular level of performance may differ from frequency sub-band to frequency sub-band. Whereas DSSS signal occupies the entire channel band, the number of information bits per modulation symbol (i.e., the data rate) that may be transmitted using the different DSSS sequence for each spatial channel for a particular level of performance.
In the MIMO-OFDM communication system using a typical scheme, a high Peak-to-Average Power Ratio (PAPR) may be caused by the multiple carrier modulation. That is, because data are transmitted using multiple carriers in the MIMO-OFDM scheme, the final OFDM signals have amplitude obtained by summing up amplitudes of each carrier. The high PAPR results when the carrier signal phases are added constructively (zero phase difference) or destructively (±180 phase difference). Notably, OFDM signals have a higher PAPR than single-carrier signals do. The reason is that in the time domain, a multicarrier signal is the sum of many narrowband signals. At some time instances, this sum is large and at other times is small, which means that the peak value of the signal is substantially larger than the average value. Similarly, MIMO-DSSS schemes can have high PAPR for periodic sequence or binary-valued sequence; however, chaos spreading sequences do not exhibit either of these characteristics and therefore have better PAPR performance for SISO and MIMO operations.
Common PAPR reduction strategies include amplitude clipping and filtering, coding, tone reservation, tone injection, active constellation extension, and multiple signal representation techniques such as partial transmit sequence (PTS), selective mapping (SLM), and interleaving. These techniques are often implement at a sampling rate at least four times the baseband signal rate and can achieve significant PAPR reduction, but at the expense of transmit signal power increase, bit error rate (BER) increase, data rate loss, increase in computational complexity, and so on. Further, many of these techniques require the transmission of additional side-information (about the signal transformation) together with the signal itself, in order that the received signal to be properly decoded. Such side-information reduces the generality of the technique, particularly for a technology where one would like simple mobile receivers to receive signals from a variety of base station transmitters. Alternatively, properly designed chaos spreading sequences can be utilized as a phase dithering sequence added to MIMO-OFDM and SISO-OFDM composite carrier signal to reduce PAPR and send side-information about the signal transformation without substantially increasing transmit signal power or degrading the BER at the receiver.
In many regions, there will be the desire for heterogeneous network such as MIMO-OFDM system and Digital Chaos Cooperative Network to share a common band of frequency to alleviate the “spectrum crunch” being experienced by the overwhelming demand for data in the finite radio frequency spectrum. One such approach to handle this coordination or sharing is dynamic spectrum access (DSA). In DSA networks that consider different degrees of interaction between primary users and secondary users, it is desired to control out-of-bound interference (i.e., “emissions”) between primary user's transmissions and secondary user's transmissions. In DSA networks including underlay transmission, secondary users may communicate with each other as long as the interference created to the primary user is below some predefined threshold. In this case, the secondary users not only assess whether primary users are transmitting but also how much interference or emissions they will create and whether this will disrupt the primary user's transmission. In a DSA network having overlay transmissions the primary user and the secondary user are permitted to communicate in a cooperative fashion. In any DSA network including underlay transmission and the overlay transmissions, or in DSA networks having a combination of overlay and underlay networking, it is necessary to assess the impact of the presence of secondary users on primary user transmissions for total efficient transmission.
The term “dynamic spectrum access” has broad connotations in spectrum and regulatory body communities to encompass various approaches to spectrum reform. One such reform of interest related to the present invention is the category of Hierarchical Access Model, based on primary and secondary users. In one embodiment of the present invention, the primary user transmission conforms to SISO OFDM system and secondary user transmission conforms to SISO digital chaos cooperative network. In yet another embodiment, the primary user transmission conforms to MIMO or MISO OFDM system with MIMO or MISO digital chaos cooperative network. Typical examples of secondary user operations involve controlling out-of-bounds emissions or interference based on the composite PAPR of a transmitting station engaged in concurrent primary user and secondary user operations. In this instance, “concurrent” may mean that the primary user stream and the secondary stream are transmitting simultaneously out of the same antenna structure. The “composite PAPR” is calculated using signals from each primary user and secondary user and calculating a total PAPR for the collection of primary and secondary users. Secondary user operations include secondary user transmissions in a dynamic spectrum access network (DSA). Overlay signal transmissions and underlay signal transmissions are examples of secondary user transmissions found in DSA networks, which can be controlled based on evaluation of the composite PAPR and one other constraint according to this invention.
The continually increasing reliance on multi-carrier SISO and especially MISO wireless forms of communication creates reliability, PAPR and privacy problems. Data should be reliably transmitted from a transmitter to a receiver. In particular, the communication should be resistant to noise, interference, and possibly to interception by unintended parties. Many PAPR reduction techniques lead to distortion the transmit signal characteristics, which is quantifiable by Error-Vector-Magnitude (EVM) and out-of-band spectral emissions. The goal of prior art and a subject of this invention is to minimize the effect on EVM and out-of-band spectral emission while reducing PAPR, which allows use of higher order modulation scheme to result in higher spectral efficiencies for the network. The error vector magnitude is a measure used to quantify the performance of a digital radio transmitter or receiver. A signal sent by an ideal transmitter or received by a receiver would have all constellation points precisely at the ideal locations, however various imperfections in the implementation (such as carrier leakage, low image rejection ratio, phase noise etc.) cause the actual constellation points to deviate from the ideal locations. Informally, EVM is a measure of how far the points are from the ideal locations. An error vector is a vector in the real and imaginary plane between the ideal constellation point and the point received by the receiver. In other words, it is the difference between actual received symbols and ideal symbols. The average power of the error vector, normalized to signal power, is the EVM. For the percentage format, root mean square (RMS) average is used; that is, the square root of the arithmetic mean of the squares of the signal amplitudes, or the square of the function that defines the continuous waveform. In comparison, out-of-band spectral emission is predicated on the definition of what is considered the occupied bandwidth of the incoming signal. One common definition used in the art is the 99% occupied bandwidth, which is defined as the bandwidth that contains 99% of the total power of the signal. Governing regulatory body of the countries define a spectrum mask of allowable power relative to the total power that a device may transmitter in specified frequency bandwidths at certain offsets from the center of the occupied bandwidth. The out-of-band spectral emission is defined as the accumulative measured power starting at a frequency offset of 0.5 times the occupied or necessary bandwidth and extends up to 2.5 times the occupied or necessary bandwidth, respectively. In the present invention, a fitness function is constrained by the allowable over-drive level while meeting the linearity mask, which is adaptively estimated by an adjacent channel leakage ratio (ACLR) sensing algorithm, incorporated in the transmitter, that utilizes input drive signal power to the PA.
In the last few years there has been a rapidly growing interest in ultra-wide bandwidth (UWB) impulse radio (IR) communication systems. These systems make use of ultra-short duration pulses that yield ultra-wide bandwidth signals characterized by extremely low power spectral densities. UWB-IR systems are particularly promising for short-range wireless communications as they combine reduced complexity with low power consumption, low probability of detection (LPD), immunity to multipath fading, and multi-user capabilities. Current UWB-IR communication systems employ pseudo-random noise (PN) coding for channelization purposes and pulse-position modulation (PPM) for encoding the binary information.
Others have proposed periodic sequences of pulses in the context of chaos-based communication system. Additional work has relied upon the self-synchronizing properties of two chaotic systems. In such a system, data is modulated into pulse trains using variable time delays and is decodable by a coherent receiver having a chaotic generator matched to the generator used in the transmitter. Such system is known in the art as a Chaotic Pulse Position Modulation (CPPM) scheme.
Such chaotic dynamical systems have been proposed to address the problem of communication privacy. Chaotic signals exhibit a broad continuous spectrum and have been studied in connection with spread-spectrum applications. The irregular nature of a chaotic signal makes it difficult to intercept and decode. In many instances a chaotic signal will be indistinguishable from noise and interference to receivers not having knowledge of the chaotic signal used for transmission. In the context of UWB systems the use of non-periodic (chaotic) codes enhances the spread-spectrum characteristics of the system by removing the spectral features of the signal transmitted. This results in a lower probability of interception/detection (LPI/LPD) and possibly less interference towards other users. This makes the chaos-based communication systems attractive.
There remains a need for improved chaotic coding/modulation methods to produce such attractive communication systems. One prior art, U.S. Pat. No. 6,882,689, issued Apr. 15, 2005 to Maggio et al., attempts to improve chaotic coding using pseudo-chaotic coding/modulation method that exploits the symbolic dynamics of a chaotic map at the transmitter to encode data. The method uses symbolic dynamics as “coarse-grained” description of the evolution of a dynamic system. The state space is partitioned and a symbol is associated with each partition. The Maggio invention uses a trajectory of the dynamic system and analyzes it as a symbolic system. A preferred transmitter of the Maggio prior art accepts digital data for coding and the digital data is allocated to symbolic states according to a chaotic map using a shift register to approximate the Bernoulli shift map acting as a convolution code with a number of states equal to the symbolic states defined on the chaotic map. The pseudo-chaotically coded data is converted to analog form and modulated into synchronization frames in a transmitted signal.
The Maggio prior art has limitations in that it uses only one chaos map (e.g., Bernoulli shift map), that is generated based on the data transmitted. By confining the mapping to Bernoulli shift, information that is repeated in each transmission or a repeat symbol can be recognized after observing the waveform over an extended period of time. Once compromised, all future data will be detectable and decodable by a hostile system.
Another prior art system that teaches a chaotic coding/modulation method is described in U.S. application Ser. No. 13/190,478 (“the '478 Patent”), which is commonly invented by the present inventor, and incorporated herein by reference in its entirety. The '478 Application teaches a system, device and method for wirelessly transmitting data via a digital chaos spreading sequences. The '478 Application system teaches constructing and storing a digital chaos spread code sequence in a volatile memory in both the transmitter and the receiver. Information corresponding to the chaos spread code sequence used to transmit the digital information is received by a receiver for identifying which chaos spread code sequence to use to retrieve the coded information. The '478 Application system further eliminates the reliance on the Bernoulli shift map, and therefore teaches a system which is less detectable by a hostile system.
While the system of the '478 Application solves many of the problems in the prior art, the system has limited applicability to SISO systems. The receiver disclosed in the '478 Application detects and processes one data stream for a single user even in the presence of other users or external interference. The '478 Application therefore would not be useful for transmission systems that jointly processes a plurality of signals detected at the receiver. For example, the joint processing of multiple signals allows for increased capacity and enhanced reception of a MIMO system.
Generally, the most fundamental issue in wireless communication lies in how efficiently and reliably data can be transmitted through a channel. The next generation multimedia mobile communication system, which has been actively researched in recent years, requires a high speed communication system capable of processing and transmitting various forms of information such as images and wireless data, different than an initial communication system providing a voice-based service.
Then according to the prior art, what is needed is a system and method that does not sacrifice data rate in favor of range, provides increased robustness, while improving LPI/LPD. A system and method is further needed that does exhibit the same positive improvements in a system detecting and receiving multiple signals.
Moreover, cooperation amongst wireless mobile units is often required in mobile ad-hoc networks (MANETs) to support the arbitrary organization of mobile units as the wireless mobile units are allowed to move randomly within a packet radio network. The nodes (e.g., wireless mobile units) of the MANET network must find a way to communicate without knowledge of the network topology that is the foundation for requiring cooperation among the nodes. The nodes of the network must learn the transmit and receive schedules of neighboring nodes to communicate. The communications between nodes is complicated by the mobile nature of the nodes. Discovery of neighboring nodes' schedules entails individual group formations, membership assignment, and broadcast messaging capability to disseminate the essential health of the group to members and, potentially, non-members for certain circumstance. The rate of resolving the scheduling must be fast and bandwidth efficient such that the network can be stabilized yet updated often enough such that the information collected has not become stale. Therefore, the lightness in overhead and relative speed of generating the channel schedules become important factors in the design of the Media Access Control (MAC) layer in cooperative network. A number of the unique characteristics of digital chaos signal structure simplifies these operations compared to prior art. In particular, the property that several digital chaos signals can simultaneously exist on the medium without causing a collision greatly reduces the time need to disseminate group health or status information to all members of the group and hence changes the method of discovery for the schedule of neighboring nodes. Another property that help reduces the number of exchanges in handshaking between nodes is that a unique broadcast digital chaos signature derived from a device's unique identifier, such as unique 15-digit IMEI or ‘International Mobile Equipment Identity’ number, is preload in the devices non-volatile memory. Since the IMEI is unique for each cellular device, the association and authentication process can be performed simpler and more secure than the prior art for similar process steps in other radio protocols. Lastly, the orthonormal property of the digital chaos signals allows channel sensing to be perform on a per user basis as well as the total users occupying the media at the time.